This disclosure relates to image compression and decompression and, more particularly, to inverse quantizing quantized signal samples of an image during image decompression.
As is well-known, in a variety of situations, it is desirable to have the ability to compress and decompress an image or a sequence of images. Without limitation, this may be desirable, for example, for transmission over a limited bandwidth communications channel, or for efficient storage of an image so it may later be retrieved. As is also well-known, image compression and decompression is typically computationally intensive and also employs a variety of operations in order to accomplish the end result, namely compression. For example, typically the image is transformed into another domain, such as from the spatial demain to the frequency domain, and, likewise, typically some form of quantization is employed. Likewise, to decompress, a reverse process is employed. These are just two examples of the operations that may be performed upon the signal samples of an image in order to accomplish image compression and decompression. Additional operations may include entropy encoding, etc. Typically, each of these operations are computationally intensive. Therefore, if these operations are performed in software, a relatively large amount of processing power may be employed in order to perform the compression. Likewise, if, alternatively, these operations are performed using hardware, typically, separate hardware elements may be employed to perform each operation, to pipeline the processing, for example. A need, therefore, exists to reduce the amount of computationally intensive operations or the number of separate hardware elements employed to perform image compression and decompression.